Compara

2011

With the increasing availability of metropolitan transportation data, such as those from vehicle GPSs (Global Positioning Systems) and road-side sensors, it becomes viable for authorities, operators, as well as individuals to analyze the data for a better understanding of the transportation system and possibly improved utilization and planning of the system. We report our experience in building the VAST (Visual Analytics for Smart Transportation) system. Our key observation is that metropolitan transportation data are inherently visual as they are spatio-temporal around road networks. Therefore, we visualize traffic data together with digital maps and support analytical queries through this interactive visual interface. As a case study, we demonstrate VAST on real-world taxi GPS and meter data sets from 15, 000 taxis running two months in a Chinese city of over 10 million population. We discuss the technical challenges in data cleaning, storage, visualization, and query processing, and offer our first-hand lessons learned from developing the system.

2018

The widespread use of urban software and information technology infrastructure systems now demand new levels of complexity in data generation and data application across interoperating domains. Given this context, and discoveries in visual analytics research that reveal knowledge is created, verified, refined and shared through the interactive manipulation of the visualization (Pike et al. 2009), defining a taxonomy of visualizations can assist visualization system designers in understanding key visualization techniques that serve multiple linked user groups (Chengzhi et al. 2003). It could also be meaningful to others working in sectors that are now in the process of interoperating through the pervasive nature of digital economies. Understanding the potential components of a taxonomy for these forms of data visualization demands the identification of inter-relating and diverse user groups utilizing the same data for multiple tasks (Mahyar et al. 2015), the complexity of visualizati...

Lecture Notes in Computer Science book series (LNCS, ), International Conference on Distributed, Ambient, and Pervasive Interactions DAPI 2016: Distributed, Ambient and Pervasive Interactions , 2016

Existing technologies for transportation planning, urban design, and decision-making have not kept pace with rapid urbanization. Visualization and analysis tools can help by combining qualitative, quantitative, and historical urban data – helping experts understand the system of systems of the modern city. Incorporating insights from experts in several relevant fields, we have derived a performance specification for visualization tools supporting general transportation planning problems . We examine two existing technologies against the specification – Betaville and StoryFacets – and recommend adapting them as first-generation urban system analysis/planning support tools. We also suggest guidelines for the next generation of tools for transportation planning.

2019

1 ABSTRACT Today different sources of information on urban are as are becoming openly available at various spatial nd temporal resolutions and extents. They are crucial for driving towards “Smart Cities”. Many smart city relevant applications, to understand and predict ce rtain phenomena such as mobility, air quality, etc. , depend on large amounts of readily available good quality data. Many datasets related to such topics are alre ady publicly available. However, the appropriate use of these datasets must be ensured by checking the qua lity of data in a systematic way. Under quality of data, on e not only evaluate the number of missing or false data points but also determine data characteristics such as resolution, frequency and ease of use, etc. The refor , the objectives of this paper are to evaluate the op n data available in different portals (80 in total ) with special consideration to these factors and to evalu ate their usability in some of the smart city appli cations. In ...

Handbook of Research on Social, Economic, and Environmental Sustainability in the Development of Smart Cities

This chapter introduces a range of analytics being used to understand the smart city, which depends on data that can primarily be understood using new kinds of scientific visualisation. We focus on short term routine functions that take place in cities which are being rapidly automated through various kinds of sensors, embedded into the physical fabric of the city itself or being accessed from mobile devices. We first outline a concept of the smart city, arguing that there is a major distinction between the ways in which technologies are being used to look at the short and long terms structure of cities, and we then focus on the shorter term, first examining the immediate visualisation of data through dashboards, then examining data infrastructures such as map portals, and finally introducing new ways of visualising social media which enable us to elicit the power of the crowd in providing and supplying data. We conclude with a brief focus on how new urban analytics is emerging to m...

Proceedings of the Design Society, 2021

Massive data are surrounding us in our daily lives. Urban mobility generates a very high number of complex data reflecting the mobility of people, vehicles and objects. Transport operators are primary users who strive to discover the meaning of phenomena behind traffic data, aiming at regulation and transport planning. This paper tackles the question "How to design a supportive tool for visual exploration of digital mobility data to help a transport analyst in decision making?” The objective is to support an analyst to conduct an ex post analysis of train circulation and passenger flows, notably in disrupted situations. We propose a problem-solution process combined with data visualisation. It relies on the observation of operational agents, creativity sessions and the development of user scenarios. The process is illustrated for a case study on one of the commuter line of the Paris metropolitan area. Results encompass three different layers and multiple interlinked views to ex...

The advancement of sensor technologies makes it possible to collect large amounts of dynamic urban data. On the other hand, how to store, process, and analyze collected urban data to make them useful becomes a new challenge. To address this issue, this paper proposes a visual analytics framework, which is applied to transportation data to manage and extract information for urban studies. More specifically, the proposed framework has three components: (1) a geographic information system (GIS) based pipeline providing basic data processing functions; (2) a spatial network analysis that is integrated into the pipeline for extracting spatial structure of urban movement; (3) interactive operations allowing the user to explore and view the output data sets at different levels of details. Taking Singapore as a case study area, we use a sample data set from the automatic smart card fare collection system as an input to our prototype tool. The result shows the feasibility of proposed framework and analysis method. To summarize, our work shows the potential of geospatial based visual analytics tools in using 'big' data for urban analysis.

ISPRS Annals Photogrammetry, Remote Sensing and Spatial Information Sciences, III-4/W1

As many cities increase in size across multiple dimensions such as population, economic output and physical size, new methods for understanding and managing cities are required. Data produced by and about urban environments offer insight into what is happening in cities. Real-time data from sensors within the city record current transport and environmental conditions such as noise levels, water levels, journey times and public transport delays. Similarly administrative data such as demographics, employment statistics, property prices and crime rates all provide insight into how a city is evolving. Traditionally, these data were maintained separately and managed by individual city departments. Advances in technology and a move to open-government have placed many of these data in the public domain. Urban dashboards have emerged as a technique to visualise these data in an accessible way. This paper describes the implementation of one such dashboard, the Dublin Dashboard, an interactive website which collects, analyses and visualises data from a variety of sources about Dublin in Ireland through a series of interactive maps, graphs and applications. This paper describes the approach, the data and the technology used to develop the Dublin Dashboard and acts as a guideline for developing urban dashboards in other cities.

2017 Winter Simulation Conference (WSC), 2017

The CitScale tool is a software platform for visualizing, analyzing and comparing the impacts of smart city policies based on innovative mobility concepts in urban areas. It places emphasis on new automotive vehicles aimed at reducing traffic or environmental impacts. This paper introduces this traffic simulation-based tool, and two case studies developed for different scenarios in Barcelona City are briefly presented to demonstrate the capabilities of the tool when it is combined with microscopic traffic simulation software. The first case presents an extensive evaluation of new innovative vehicles (electric vehicles, bikes and three-wheeled scooters) and mobility concepts (trip-sharing). In the second one, data provided by connected cars is analyzed in order to compare different developed navigation strategies and how they affect the city. Finally, some of the obtained results from both cases are concisely presented in order to show the potential of the proposed tool.